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- W4211199820 abstract "Cell fate decisions play pivotal roles in many fundamental biological processes such as cell differentiation, tissue reprogramming, and cancer metastasis. Computational trajectory inference using single-cell RNA sequencing data enables the discovery of cell states and state transitions. Here we present a novel method combining trajectory inference with the direction information derived from the stochastic models of the process of RNA transcription. Our approach treats cell state transition as a probabilistic process, automatically distinguishes initial starting states and the terminal states, and further delineates the underlying trajectories of cellular differentiation." @default.
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- W4211199820 date "2022-02-01" @default.
- W4211199820 modified "2023-09-30" @default.
- W4211199820 title "Defining cell states and unraveling cell states transition through models of stochastic dynamics during differentiation" @default.
- W4211199820 doi "https://doi.org/10.1016/j.bpj.2021.11.2058" @default.
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